Update model.py

model.py

@@ -150,32 +150,3 @@ def getLayersOutDet(self):
 
 def reparameter(mu,sigma):
     return (torch.randn_like(mu) *sigma) + mu
-
-class AttDec(nn.Module):
-    def __init__(self, opt, attSize):
-        super(AttDec, self).__init__()
-        self.embedSz = 0
-        self.fc1 = nn.Linear(opt.resSize + self.embedSz, opt.ngh)
-        self.fc3 = nn.Linear(opt.ngh, attSize)
-        self.lrelu = nn.LeakyReLU(0.2, True)
-        self.hidden = None
-        self.sigmoid = None
-        self.apply(weights_init)
-
-    def forward(self, feat, att=None):
-        h = feat
-        if self.embedSz > 0:
-            assert att is not None, 'Conditional Decoder requires attribute input'
-            h = torch.cat((feat,att),1)
-        self.hidden = self.lrelu(self.fc1(h))
-        h = self.fc3(self.hidden)
-        if self.sigmoid is not None: 
-            h = self.sigmoid(h)
-        else:
-            h = h/h.pow(2).sum(1).sqrt().unsqueeze(1).expand(h.size(0),h.size(1))
-        self.out = h
-        return h
-
-    def getLayersOutDet(self):
-        #used at synthesis time and feature transformation
-        return self.hidden.detach()